Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hoavdc/codexkit/codexkit-brand-positioning-canvasnpx skills add hoavdc/CodexKit --skill codexkit-brand-positioning-canvasgit clone --depth 1 https://github.com/hoavdc/CodexKitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hoavdc/codexkit/codexkit-brand-positioning-canvas)<a href="https://agentmods.dev/skills/hoavdc/codexkit/codexkit-brand-positioning-canvas"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-brand-positioning-canvas.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00069 | $0.00661 |
| Opus 5 | $0.00034 | $0.00331 |
| Sonnet 5 | $0.00014 | $0.00132 |
| Haiku 4.5 | $0.00007 | $0.00066 |
Grade A, and why
codexkit-brand-positioning-canvas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Positioning Canvas
Purpose
Create a positioning foundation that sharpens how a brand should show up and what it should claim.
When to use
- A product or brand needs sharper differentiation.
- A campaign or launch lacks a strategic messaging base.
- A team needs shared language for audience, value, and proof.
When not to use
- The request is only to rewrite one headline or ad line.
- No audience, category, or competitor context exists at all.
Inputs
- product or service offer
- target audience and known customer signals
- competitors or substitutes
- proof points, credibility assets, and brand tone
- business goals for the positioning work
Procedure
- Define the audience and the job they are trying to get done.
- Clarify the category and what alternatives customers compare against.
- Surface the few differentiators that are both meaningful and provable.
- Translate that into a positioning statement, brand voice, and message pillars.
- State what the brand is not, to avoid mushy positioning.
- Flag claims that lack proof or strategic focus.
Output
- positioning canvas
- target audience and JTBD summary
- differentiators and reasons to believe
- tone and message pillars
- anti-positioning or "not us" guardrails
Definition of done
- Differentiation is explicit and supportable.
- The output can guide messaging beyond one campaign.
- The team can see what claims to avoid.
Examples
- "Help us position our B2B product against two bigger competitors."
- "Build a positioning canvas we can use before rewriting the website."
Quality Criteria
- All claims reference specific frameworks, standards, or quantifiable data
- Content matches the stated audience's expertise level
- Recommendations are actionable — each includes a concrete next step
- No unsupported assertions or generic filler language
Verification (4C)
| Check | Question |
|---|---|
| Correctness | Do referenced frameworks and standards match their official definitions? |
| Completeness | Are all key concepts covered without significant gaps for the stated audience? |
| Context-fit | Would this be useful for someone new to this domain, or is it too advanced/too basic? |
| Consequence | If a stakeholder acted on this immediately, what could they misinterpret? |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 86 lines · 69 tokens per session scan A 60e0a31c9efe
codexkit-brand-positioning-canvas is a skill published in the GitHub repository hoavdc/CodexKit (21 stars, last pushed 3mo ago), licensed MIT. It adds 69 tokens to every session and 661 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
knowledge_base
Manage the user's personal knowledge base — knowledge graph, documents, and wiki vault.
reducing-aigc-detection
Systematically reduce AIGC detection rates in academic papers (Chinese/English). Analyzes detection reports, identifies high-impact sections, applies multi-layer rewriting strategies preserving formatting/footnotes, and verifies results. Supports 维普/知网/Turnitin platforms.
architecting-security
安全架构与治理：威胁建模 (STRIDE/PASTA/LINDDUN)、零信任身份架构、IAM/SSO/MFA/PAM、合规框架 (SOC2/PCI/HIPAA/GDPR)、DLP、隐私工程、安全控制设计。Use when designing security architecture, threat modeling new systems, implementing zero-trust identity, designing IAM/SSO/PAM, building compliance evidence chains, or planning privacy-by-design.
defending-applications
Application security defense knowledge for builders. Covers Web/API/GraphQL hardening (XSS/SQLi/SSRF/IDOR/BOLA/Mass Assignment/deserialization/upload/path traversal), authentication/authorization (OAuth 2.0/OIDC/JWT/Session/Cookie/SAML/SSO), and LLM application security (prompt injection, jailbreak, RAG poisoning…
detecting-and-responding
蓝队与紫队工程：检测规则编写、SIEM/EDR 调优、事件响应、数字取证、威胁狩猎、ATT&CK 映射、紫队演练闭环。Use when writing Sigma/YARA detection rules, tuning SIEM noise, responding to security incidents, conducting forensic analysis, hunting threats, or running purple team exercises.
securing-cloud-and-supply-chain
云原生与软件供应链安全防御。容器/K8s 加固、Service Mesh、CI/CD 安全、SLSA/SBOM/Sigstore、云 IAM、Secrets 管理、IaC 安全。Use when hardening Kubernetes clusters, auditing CI/CD pipelines, implementing supply chain security, managing cloud IAM, or reviewing IaC code.